AI SOC: Key to Solving Persistent SOC Challenges

This is a guest blog post by Jon Hencinski. Jon is the Sr. Director of Security Operations at Workday. Previously, he was the VP of Security Operations at Expel and VP of Operations at Fixify.

At the core of every organization's cyber defense stands the Security Operations Center (SOC)—a dedicated team of people empowered by technology and streamlined processes. Their mission is straightforward yet formidable: to rapidly detect and respond to security threats, mitigating harm effectively.

As technology evolves, so does the attack surface. New devices, applications, and services continuously introduce vulnerabilities that cyber adversaries are eager to exploit. Efficient security operations have never been more critical, yet persistent challenges often hinder the SOC's optimal performance.

But imagine a different reality. Picture SOC analysts unburdened by repetitive tasks and free from alert fatigue. Envision threats detected and neutralized in real time, with artificial intelligence acting as a powerful ally. Thanks to recent advancements in AI—particularly large language models (LLMs) and AI agents—this vision is swiftly becoming a reality. These technologies are revolutionizing SOC operations, tackling challenges that once seemed insurmountable.

Persistent SOC challenges

The daily grind of alert overload

SOCs often fall into the trap of trying to detect every possible threat, generating an overwhelming number of alerts—many of which are false positives or low-priority issues. This flood leads to alert fatigue among analysts, increasing the risk of overlooking genuine threats.

A common misstep is striving for full coverage of frameworks like MITRE ATT&CK without prioritizing based on the organization's unique risk profile and existing preventive controls. Instead of focusing on areas where defenses are weakest and deploying targeted detection controls, organizations attempt to cover all threats equally. This dilutes efforts and strains resources unnecessarily.

Adding to the problem, companies frequently purchase new security tools without properly configuring them or tailoring alerts to their specific environment. Onboarding these tools without an aligned detection strategy results in a barrage of irrelevant alerts, further taxing the SOC's capacity and effectiveness.

Overwhelming repetitive tasks

Alerts not only overwhelm by volume but also burden analysts with repetitive, mundane tasks. When an alert triggers, analysts often pivot between multiple tools, manually gathering additional information to make informed decisions. For instance, a suspicious login alert from an identity provider might require several steps: checking user activity logs, verifying access patterns, and cross-referencing data across various security platforms.

This manual process is time-consuming and mentally exhausting. The tedious repetition drains analysts' energy, pulling them away from higher-level tasks that could significantly enhance the organization's security posture. 

Lack of decision support

Closely tied to repetitive tasks is the absence of adequate decision support for analysts. SOC teams often operate in a binary mode, seeking absolute certainty before taking action—a quest that's both unrealistic and counterproductive in the dynamic landscape of cybersecurity.

Analysts need tools that empower them to make risk-based decisions, guiding them through nuanced scenarios where activities might deviate from typical patterns. It's acceptable—and sometimes necessary—to err on the side of caution and overreact to an alert. However, without proper decision support systems, analysts struggle to make these judgments efficiently, leading to delays and potential oversights that increase risk for the organization. 

Analyst burnout

Attempting to detect everything, neglecting to automate repetitive tasks, and failing to equip analysts with decision support tools create a perfect storm for burnout. Overworked and under-supported analysts are more susceptible to fatigue and errors, compromising security and increasing turnover rates. Ironically, some organizations aren't even aware they're operating beyond their capacity.

Understanding capacity versus utilization is crucial because human time is the ultimate constraint. Without a clear grasp of available analyst time, organizations can't make informed decisions about resource allocation. SOCs must develop and use capacity models to manage human resources effectively. Without this insight, they risk overloading analysts, missing critical alerts, and failing to justify investments in new security tools.

AI as the catalyst for transformation

Artificial intelligence emerges as a powerful solution to these persistent challenges. Integrating AI into SOC operations isn't just about automating tasks; it's about enhancing the entire ecosystem—people, processes, and technology.

Measurable results through AI integration

To tackle these challenges, AI must deliver tangible improvements. Focusing on measurable outcomes allows organizations to assess effectiveness and directly address issues like alert overload, repetitive tasks, lack of decision support, and analyst burnout. Key areas where AI can make a significant impact include:

• Lower Risk: Enhanced detection capabilities and decision support reduce the likelihood of successful attacks and breaches.
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• Accelerated Response Times: By automating repetitive tasks and swiftly providing critical information, AI improves decision-making and shifts the SOC from reactive to proactive.
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• Reduced Repetitive Tasks: AI handles routine processes like crafting SIEM queries and gathering data, freeing analysts to focus on nuanced decisions and strengthen relationships within the organization—reducing burnout.
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• Enhanced Decision Support: AI offers intelligent insights and context, aiding analysts in making risk-based decisions confidently, even amid uncertainty.
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• Improved Scalability: With AI managing routine tasks, the SOC can accomplish more with existing resources, effectively addressing capacity constraints without adding staff.
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• Overall SOC Efficiency: AI streamlines workflows and optimizes resource utilization. Understanding and managing capacity versus utilization allows better allocation of human resources and prevents analyst overload.

By directly addressing these core challenges, AI doesn't just add technology—it transforms SOC operations, empowers analysts, and fortifies the organization's defense against cyber threats.

What will modern AI-driven SOCs look like over the next 5 years?

Analysts shift to strategic roles

AI won't remove humans from the SOC loop; it will redefine their role. Analysts will transition from overworked responders to empowered strategists. With AI managing mundane tasks, human experts can focus on complex problem-solving, threat hunting, and strategic planning. This shift boosts morale, reduces burnout, and decreases turnover rates.

Instead of triaging alerts and wrestling with tools to gather data, analysts will concentrate on nuanced, risk-based decisions. Machines excel at repetitive tasks, so AI will handle duties like running SIEM queries. When an alert fires, it becomes a decision point rather than just more work. Each decision feeds back into the system, continuously enhancing security.

Deeper insights, stronger defense

Enhanced visibility into the threat landscape will be a hallmark of AI-driven SOCs. Advanced analytics and predictive modeling will offer unprecedented insights, enabling organizations to anticipate threats and adapt defenses proactively.

Constantly learning

Future SOCs will be learning organizations. AI systems will continuously evolve, learning from previous decisions and adapting to new threats. They will provide analysts with contextual support, offering recommendations based on historical data, emerging trends, and global intelligence.

Armed with advanced decision support tools, analysts can make nuanced, risk-based judgments confidently, even amid uncertainty. This support empowers them to act decisively and err on the side of caution when necessary.

Scaling despite skills shortage

AI-driven SOCs will enable organizations to do more with existing resources. Scalability will no longer depend on adding staff. AI enables our people to scale with the security needs of the organization. 

Considerations for SOC leaders

As organizations embrace this new era, SOC leaders must be mindful of several key considerations:

• Understanding capacity and utilization: While AI enhances efficiency, it doesn't eliminate the need for human analysts. Leaders must continue to manage and allocate human resources effectively. 
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• Integration with tools and workflows: AI tools should integrate with existing security infrastructure and workflows rather than ripping and replacing current systems.
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• Trust and explainability: AI systems need to be highly transparent in order to develop trust. AI decisions should be explainable for validation.
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• Always learning and adapting: SOCs are dynamic and move fast. The AI systems must be able to learn and adapt to the needs of a SOC. This can come in the form of direct human feedback. 
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• Skill development: Analysts will require training to work effectively alongside AI, interpreting AI-driven insights and making informed decisions.
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• Ethical and responsible AI use: Ensuring that AI systems operate transparently and without bias is crucial.
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• AI security: AI systems have their own security considerations, especially around data privacy and data leakage prevention. It’s critical to understand and mitigate those risks when implementing AI systems. 

Future Outlook

The evolving role of SOC analysts

Far from rendering analysts obsolete, AI will elevate their roles to new heights. They will become "supercharged" professionals, leveraging AI to amplify their decision-making and operational impact. With routine tasks automated, analysts can dedicate their skills to areas requiring human intuition and expertise—like developing advanced security protocols and engaging in proactive threat hunting. This evolution transforms the analyst's role from reactive responder to strategic leader in cybersecurity.

Long-term benefits of an AI-infused SOC

Integrating AI into SOC operations isn't just a short-term fix—it's a transformation offering profound long-term advantages. As AI systems continuously learn and adapt, organizations will experience ongoing improvements in efficiency and effectiveness. The enhanced security posture resulting from AI augmentation empowers human analysts to focus on strategic initiatives that drive innovation and resilience. Imagine a SOC that's not merely reacting to threats but proactively staying ahead of them, all enabled by the powerful collaboration between AI and human expertise.

Conclusion

As a SOC analyst, manager, or director, you know firsthand the challenges that come with protecting your organization in an ever-evolving cyber landscape. The constant flood of alerts, the repetitive tasks, and the pressure to stay ahead of sophisticated threats can be overwhelming. But it doesn't have to be this way.

AI offers you the tools to alleviate the burdens that burden your analysts. It automates the mundane, enhances decision-making, and scales with growing demands. This isn't about replacing the human element; it's about elevating it. With your team's expertise amplified by AI's capabilities, you can propel your organization to the forefront of cybersecurity. 

Further reading

‍‍SOC metrics that matter‍
‍Top 3 scenarios for auto remediation
‍‍Automated incident response: streamlining your SecOps
‍‍Key SOC tools every security operations needs‍
‍Demystifying SOC automation‍
‍Alert triage and investigation in cybersecurity: best practices‍
‍SOC analyst challenges vs SOC manager challenges‍
‍Alert tuning best practices: keys to reducing false positives
‍‍How to investigate Okta alerts
AI SOC Analyst: A comprehensive guide